Stability control represents one of the most challenging tasks in autonomous vehicle dynamics. Within this context, model uncertainty may play a crucial role in determining the quality of the overall control system. In this work, we deal with nonlinear vehicle stability control design by using the D2-IBC (Data Driven - Inversion Based Control) method, wherein the dynamics of the system are modeled from data not to optimize the open-loop model matching but to maximize the closed-loop performance. Specically, a multivariable extension of the method is derived and discussed in detail as far as the stability control application is concerned. This method will prove its eectiveness on a multi-body simulator of a 4-wheel steering autonomous vehicle.
Nonlinear stability control of autonomous vehicles: a MIMO D2-IBC solution / O., Galluppi; S., Formentin; Novara, Carlo; S. M., Savaresi. - (2017), pp. 3754-3759. (Intervento presentato al convegno 20th IFAC World Congress tenutosi a Toulouse, France).
Nonlinear stability control of autonomous vehicles: a MIMO D2-IBC solution
NOVARA, Carlo;
2017
Abstract
Stability control represents one of the most challenging tasks in autonomous vehicle dynamics. Within this context, model uncertainty may play a crucial role in determining the quality of the overall control system. In this work, we deal with nonlinear vehicle stability control design by using the D2-IBC (Data Driven - Inversion Based Control) method, wherein the dynamics of the system are modeled from data not to optimize the open-loop model matching but to maximize the closed-loop performance. Specically, a multivariable extension of the method is derived and discussed in detail as far as the stability control application is concerned. This method will prove its eectiveness on a multi-body simulator of a 4-wheel steering autonomous vehicle.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2677293
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